Project abstract for group beilman

Using Metabolomics to Profile or Find Potential Biomarkers in Various States of Disease or Trauma

These researchers work with the Center for Mass Spectrometry and Proteomics to obtain and analyze mass spectrometry data from plasma samples in various disease states. MSI resources are required to process and analyze these data. Current projects include:

The researchers are looking for biomarkers indicative of successful outcomes for patients who have undergone total pancreatectomy with islet auto-transplantation (TPIAT) procedures. One key outcome for these patients is insulin independence after TPIAT. Currently, the best predictor of insulin independence is islet yield, which can only be measured at the time of surgery when the pancreas is removed and processed. The researchers seek to utilize -omics strategies to search for non-invasive markers of positive outcomes that can be measured before surgery.

The group is using metabolomics to profile plasma metabolites that express a 24-hour period to assess alterations in the circadian rhythms of long-term ICU patients. Disruptions to the circadian system, which are related to interactions among sleep disturbance, the ICU environment, and critical illness itself, are well-documented. Such disruptions are believed to be associated with ICU delirium, which is a known risk factor for poor recovery from critical illness. The researchers seek to profile circadian rhythms on multiple physiologic scales to better understand the mulitfactorial nature of circadian system disruption in the ICU, as well as to assess the efficacy of interventions aimed at re-consolidating the circadian rhythm in these patients.

The researchers seek to correlate plasma and stool metabolomes to microbiomes of patients receiving different opioids for pain management. It has been demonstrated that certain opioids are disruptive to the microbiome. Further, disruptions to the microbiome may be related to complicated recovery from surgery. The researchers want to characterize the role that different opioids play in disruption to the microbiome, and to correlate that disruption to biomarkers in stool and plasma that can be used to guide optimal opioid therapy.